SCADA SYSTEM TRENDS IN DEEPWATER DEVELOPMENTS

ABSTRACT

Subsea systems used in combination with host facilities, such as floating, production storage and offloading units (FPSOs), tension leg platforms (TLPs), spars or compliant towers employ supervisory control and data acquisition (SCADA) systems whose architectures differ from SCADA systems found on conventional platforms. In these systems, programmable logic controllers (PLCs) located on the host facility, provide control of subsea valves on manifolds and satellite wells. PLCs also continuously record data from temperature and pressure sensors located on subsea wells. Since it is expensive to repair the electronic systems on the manifolds and satellite wells, redundancy is typically built into the system.

SCADA systems used in deepwater must also provide for control switching to workover vessels. Such vessels must provide control compatible with the existing deepwater multiplex controls and must ensure the safe control of the well.

During 1999, the Minerals Management Service (MMS) in the United States launched a study to assess the current state of SCADA systems used in the territorial waters of the US, with special emphasis on quantifying the reliability of these systems.

This paper describes findings from this study and provides a comparison of trends with other international deepwater SCADA systems.

INTRODUCTION

Deepwater developments have progressed from fixed structures in waters of less than 1400 feet to developments that include an array of structures (FPSO, TLP, Spar) in water depths of 4000 feet or more.

At the same time, subsea well technology has become sufficiently advanced to allow wells to be completed on the seafloor in over 5000 feet of water. Multiplex electro-hydraulic control (MUX) systems interface these subsea wells with the host platform and provide the ability to close valves, sample well pressures and temperatures, test well flow, run shut-in pressure surveys and to control well treatments.

SCADA systems have also evolved from discrete stand-alone systems, to systems integrating a multitude of input and output points through the use of PLCs and PC-based controllers. These modern SCADA systems provide the capability to continuously monitor subsea wells, poll the wells for status of operation, sample and return data on a continuous basis, and provide emergency shut-down controls.

The United States MMS recognized these trends, and the proliferation of SCADA systems being used offshore. In 1999, the MMS initiated a study to determine the state of SCADA systems used offshore and the reliability of these systems. This work identified different SCADA architectures for fixed structures, deepwater developments, pipelines and mobile drilling units. The results reported here focus on deepwater SCADA systems.

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Shari Dunn-Norman1, Kelvin.T. Erickson 2, Egemen K. Cetinkaya3 E. Keith Stanek4 and Ann Miller5

Copyright 2000, Brazilian Petroleum Institute - IBP

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Robotic Mapping: A Survey

ABSTRACT

This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping. It describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems. The history of robotic mapping is also described, along with an extensive list of open research problems.

Keywords: Bayes filters, robotic mapping, exploration, expectation maximization algorithm, Kalman filters, mobile robots

INTRODUCTION

Robotic mapping has been a highly active research area in robotics and AI for at least two decades. Robotic mapping addresses the problem of acquiring spatial models of physical environments through mobile robots. The mapping problem is generally regarded as one of the most important problems in the pursuit of building truly autonomous mobile robots. Despite significant progress in this area, it still poses great challenges. At present, we have robust methods for mapping environments that are static, structured, and of limited size. Mapping unstructured, dynamic, or large-scale environments remains largely an open research problem.

This article attempts to provide a comprehensive overview of the state of the art in robotic mapping, with a focus on indoor environments. Virtually all state-of-the-art robotic mapping algorithms are probabilistic. Some algorithms are incremental, and hence can be run in real time, whereas others require multiple passes through the data. Some algorithms require exact pose information to build a map, whereas others can do so using odometry measurements. Some algorithms are equipped to handle correspondence problems between data recorded at different points in time, whereas others require features to carry signatures that makes them uniquely identifiable.

When writing this article, we tried to keep the level of mathematics at a minimum, focusing instead on the intuition behind the different techniques. However, some mathematical notation was deemed necessary to communicate the basic concepts in a crisp way. The serious reader is invited to read some of the articles referenced in this paper, which discuss many of the ideas presented here in more depth.

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Sebastian Thrun February 2002 CMU-CS-02-111

School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213

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